caffe2

It extends the original Caffe framework with improved operator coverage, better Python bindings, and a portable operator library that compiles for iOS, Android, Windows, and embedded Linux enabling the same model to run across the full spectrum from cloud servers to mobile apps.

The framework's operator-level modularity means that inference deployments can include only the operators needed for a specific model, keeping binary size small for mobile applications.

Caffe2 introduced ONNX (Open Neural Network Exchange) jointly with Microsoft, making it a foundational contributor to the ML model portability ecosystem. Models trained in other frameworks can be converted to Caffe2 for deployment, and Caffe2 models can be exported to ONNX for compatibility with other runtimes.

Caffe2 was merged into PyTorch as its production backend in 2018, meaning modern PyTorch users benefit from Caffe2's mobile and production-focused infrastructure through the PyTorch Mobile deployment pathway.

The original Caffe2 repository is maintained for legacy compatibility and continues to be relevant for teams with existing Caffe2 deployments.

It holds historical significance as a primary deployment framework for Facebook's production AI systems and as a co-creator of the ONNX standard that now underpins cross-framework model portability.